Current directions in digital interventions for mood and anxiety disorders

Abstract Aims There is currently no universally accepted measure for population-based surveillance of mood and anxiety disorders. As such, the use of multiple linked measures could provide a more accurate estimate of population prevalence. Our primary objective was to apply Bayesian methods to two commonly employed population measures of mood and anxiety disorders to make inferences regarding the population prevalence and measurement properties of a combined measure. Methods We used data from the 2012 Canadian Community Health Survey – Mental Health linked to health administrative databases in Ontario, Canada. Structured interview diagnoses were obtained from the survey, and health administrative diagnoses were identified using a standardised algorithm. These two prevalence estimates, in addition to data on the concordance between these measures and prior estimates of their psychometric properties, were used to inform our combined estimate. The marginal posterior densities of all parameters were estimated using Hamiltonian Monte Carlo (HMC), a Markov Chain Monte Carlo technique. Summaries of posterior distributions, including the means and 95% equally tailed posterior credible intervals, were used for interpretation of the results. Results The combined prevalence mean was 8.6%, with a credible interval of 6.8–10.6%. This combined estimate sits between Bayesian-derived prevalence estimates from administrative data-derived diagnoses (mean = 7.4%) and the survey-derived diagnoses (mean = 13.9%). The results of our sensitivity analysis suggest that varying the specificity of the survey-derived measure has an appreciable impact on the combined posterior prevalence estimate. Our combined posterior prevalence estimate remained stable when varying other prior information. We detected no problematic HMC behaviour, and our posterior predictive checks suggest that our model can reliably recreate our data. Conclusions Accurate population-based estimates of disease are the cornerstone of health service planning and resource allocation. As a greater number of linked population data sources become available, so too does the opportunity for researchers to fully capitalise on the data. The true population prevalence of mood and anxiety disorders may reside between estimates obtained from survey data and health administrative data. We have demonstrated how the use of Bayesian approaches may provide a more informed and accurate estimate of mood and anxiety disorders in the population. This work provides a blueprint for future population-based estimates of disease using linked health data.

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Crosstalk between Existential Phenomenological Psychotherapy and Neurological Sciences in Mood and Anxiety Disorders

Biomedicines ◽

10.3390/biomedicines9040340 ◽

2021 ◽

Vol 9 (4) ◽

pp. 340

Author(s):

Lehel Balogh ◽

Masaru Tanaka ◽

Nóra Török ◽

László Vécsei ◽

Shigeru Taguchi

Keyword(s):

Anxiety Disorders ◽

Biological Treatment ◽

Sense Of Self ◽

Phenomenological Approach ◽

Neurological Damage ◽

Mood And Anxiety Disorders ◽

New Interpretation ◽

And Behavior ◽

The Impact ◽

The Brain

Psychotherapy is a comprehensive biological treatment modifying complex underlying cognitive, emotional, behavioral, and regulatory responses in the brain, leading patients with mental illness to a new interpretation of the sense of self and others. Psychotherapy is an art of science integrated with psychology and/or philosophy. Neurological sciences study the neurological basis of cognition, memory, and behavior as well as the impact of neurological damage and disease on these functions, and their treatment. Both psychotherapy and neurological sciences deal with the brain; nevertheless, they continue to stay polarized. Existential phenomenological psychotherapy (EPP) has been in the forefront of meaning-centered counseling for almost a century. The phenomenological approach in psychotherapy originated in the works of Martin Heidegger, Ludwig Binswanger, Medard Boss, and Viktor Frankl, and it has been committed to accounting for the existential possibilities and limitations of one’s life. EPP provides philosophically rich interpretations and empowers counseling techniques to assist mentally suffering individuals by finding meaning and purpose to life. The approach has proven to be effective in treating mood and anxiety disorders. This narrative review article demonstrates the development of EPP, the therapeutic methodology, evidence-based accounts of its curative techniques, current understanding of mood and anxiety disorders in neurological sciences, and a possible converging path to translate and integrate meaning-centered psychotherapy and neuroscience, concluding that the EPP may potentially play a synergistic role with the currently prevailing medication-based approaches for the treatment of mood and anxiety disorders.

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Adapting a neuroscience-informed intervention to alter reward mechanisms of anorexia nervosa: a novel direction for future research

Journal of Eating Disorders ◽

10.1186/s40337-021-00417-5 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Ann F. Haynos ◽

Lisa M. Anderson ◽

Autumn J. Askew ◽

Michelle G. Craske ◽

Carol B. Peterson

Keyword(s):

Anorexia Nervosa ◽

Eating Disorder ◽

Anxiety Disorders ◽

Reward Processing ◽

Future Research ◽

Restrictive Eating ◽

Eating Disorder Symptoms ◽

Mood And Anxiety Disorders ◽

Reward Responsivity ◽

Eating Disorder Behaviors

AbstractAccumulating psychobiological data implicate reward disturbances in the persistence of anorexia nervosa (AN). Evidence suggests that individuals with AN demonstrate decision-making deficits similar to those with mood and anxiety disorders that cause them to under-respond to many conventionally rewarding experiences (e.g., eating, interacting socially). In contrast, unlike individuals with other psychiatric disorders, individuals with AN simultaneously over-respond to rewards associated with eating-disorder behaviors (e.g., restrictive eating, exercising). This pattern of reward processing likely perpetuates eating-disorder symptoms, as the rewards derived from eating-disorder behaviors provide temporary relief from the anhedonia associated with limited responsivity to other rewards. Positive Affect Treatment (PAT) is a cognitive-behavioral intervention designed to target reward deficits that contribute to anhedonia in mood and anxiety disorders, including problems with reward anticipation, experiencing, and learning. PAT has been found to promote reward responsivity and clinical improvement in mood and anxiety disorders. This manuscript will: (1) present empirical evidence supporting the promise of PAT as an intervention for AN; (2) highlight nuances in the maintaining processes of AN that necessitate adaptations of PAT for this population; and (3) suggest future directions in research on PAT and other reward-based treatments that aim to enhance clinical outcomes for AN.

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